• Proceedings of the KSR Conference
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• 2005.11a
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• pp.140-145
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• 2005

The dynamic performances of railway vehicles, such as ride comfort, stability and safety, have the opposite characteristics of response each other according to design changes of suspensions. For this reasons, it is necessary that multidisciplinary engineers join in design processes of the suspensions so as to satisfy the requirements of dynamic performance with design constraints. Sometimes iterative dynamic analyses are required so many times during the design processes. In this paper, the development of integrated process environments and the dynamic analyses of railway vehicles based on the environments are presented. Using agent and wrapping technologies, process managements about the work process and design parameters were set up under the distributed computing environments. Also, dynamic analyses on the sample railway vehicle were carried out and the efficiency and improvement in future work were discussed as results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.114-120
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• 2017

The work present in this paper deals with a navigation problem for multiple mobile robots in unknown indoor environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots' bodies must be used to detect information about the surroundings. The environments simulated in this work are dynamic ones which contain not only static but also moving obstacles. In order to guide the robot to move along a collision-free path and reach the goal, this paper presented a navigation method based on fuzzy approach. Then genetic algorithms were applied to optimize the membership functions and rules of the fuzzy controller. The simulation results verified that the proposed method effectively addresses the mobile robot navigation problem.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.825-836
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• 2019

One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.119-125
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• 2006

Distributed Systems can be defined as set of computing resources connected by computer network. One of the most significant techniques in optimization problem domains is parallel genetic algorithms, which are based on distributed systems. Since the status of dynamic network environments such as Internet and mobile computing. can be changed continually, it must not be efficient on the dynamic environments to solve an optimization problem using previous parallel genetic algorithms themselves. In this paper, we propose the effective technique, in which the parallel genetic algorithm can be used efficiently on the dynamic network environments.

• Earthquakes and Structures
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• v.11 no.6
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• pp.1043-1060
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• 2016

The engineering background of this article is an ancient wooden building with extremely high historic and cultural values in Tibet. A full understanding of the dynamic behaviour of this historic building under in-service environments is the basis to assess the condition of the structure, especially its responses to earthquake, environmental and operational loading. A dynamic monitoring system has been installed in the building for over one year and the large amounts of high quality data have been obtained. The paper aims at studying the dynamic behaviour of the wooden building in seismic and operational conditions using the field monitoring data. Specifically the effects of earthquake and crowd loading on the structure's dynamic response are investigated. The monitoring data are decomposed into principal components using the Singular Spectrum Analysis (SSA) technique. The relationship between the average acceleration amplitude and frequencies of the principle components and operational conditions has been discussed. One main contribution is to understand the health condition of complex ancient building based on large databases collected on the field.

• School Mathematics
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• v.11 no.2
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• pp.281-299
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• 2009

In this paper, we show how dynamic manipulation environments can be integrated in the mathematics curriculum by presenting some pedagogical tasks manufactured by dynamic manipulation. These examples are composed to produce meaningful definitions through inductive experiments, to strengthen the thinking ability on continuity through the visualization, to make mathematics through investigation and finding, and to strengthen the ability of posing and generalizing problems. Through these examples students can observe the process of how mathematics is being invented, and they can experience how to solve mathematical problems using physical experiments in dynamic manipulation environments. When integration of dynamic manipulation into the teaching and learning of mathematics is applied, some difficulties can come out. To resolve such difficulties, a teacher must play the role of a co-worker of students in addition to the role of a scaffolder, coach, or close listener.

• KIISE Transactions on Computing Practices
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• v.23 no.10
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• pp.605-610
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• 2017

In distributed environments, dynamic partitioning is needed to resolve the load on a particular server or the load caused by communication among servers. In heterogeneous environments, existing dynamic partitioning schemes can distribute the same load to a server with a low physical performance, which results in a delayed query response time. In this paper, we propose a dynamic partitioning scheme for large RDF data in heterogeneous environments. The proposed scheme calculates the query loads with its frequency and the number of vertices used in the query for load balancing. In addition, we calculate the server loads by considering the physical performance of the servers to allocate less of a load to the servers with a smaller physical performance in a heterogeneous environment. We perform dynamic partitioning to minimize the number of edge-cuts to reduce the traffic among servers. To show the superiority of the proposed scheme, we compare it with an existing dynamic partitioning scheme through a performance evaluation.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.181-183
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• 2006

This paper proposes an intelligent decision framework for update of the environment model using GSPN(generalized stochastic petri nets). The GSPN has several advantages over direct use of the Markov Process. The modeling, analysis, and performance evaluation are conducted on the mathematical basis. By adopting the probabilistic approach, our decision framework helps the robot to decide the time to update the map. The robot navigates autonomously for a long time in dynamic environments. Experimental results show that the proposed scheme is useful for service robots which work semi-permanently and improves dependability of navigation in dynamic environments.